Path: csiph.com!fu-berlin.de!uni-berlin.de!individual.net!not-for-mail From: Robert Klemme Newsgroups: comp.lang.java.programmer Subject: Re: How to identify outliers Date: Thu, 30 Nov 2017 18:38:02 +0100 Lines: 30 Message-ID: References: Mime-Version: 1.0 Content-Type: text/plain; charset=utf-8; format=flowed Content-Transfer-Encoding: 7bit X-Trace: individual.net s4X68dopTRPOBXKolMPKsgn/jgNSRwr5w7h8va8jjsGXUS+RY= Cancel-Lock: sha1:68HyvE+G3wsq+GmcF7FTSk1Kbz8= User-Agent: Mozilla/5.0 (X11; Linux x86_64; rv:52.0) Gecko/20100101 Thunderbird/52.4.0 In-Reply-To: Content-Language: en-US Xref: csiph.com comp.lang.java.programmer:37706 On 28.11.2017 15:40, Daniele Futtorovic wrote: > I got a statistical problem, and due to a youth math trauma, I'd like a > bit of help to solve it. :-) > I have a data series. Integer values, but that should be beside the > point. I want to identify and eliminate "outliers" from this series. > "Outliers" being values that are "too big" or "too small", in short, > that are not congruent with the rest of the series. I am well aware that > saying "outlier" begs the question, hence the quotes, but I can > fine-tune the degree of outlying for my purposes later on. For the time > being, I wonder if someone could outline some basic approaches I could > take in the matter. Funny: just today I ran across https://www.reddit.com/r/java/comments/7gkry0/statistically_rigorous_java_performance_evaluation/ and eventually found https://en.wikipedia.org/wiki/Truncated_mean which is a fairly simple and straightforward method. Depending on what you want to do you could also work with median or percentiles which are usually less affected by outliers than the median. Kind regards robert -- remember.guy do |as, often| as.you_can - without end http://blog.rubybestpractices.com/